Best practices in Analytic Network Process studies
| Autor: | Enrique Mu, Orrin Cooper, Michael C. Peasley |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Dependency (UML) Operations research Computer science Best practice Analytic network process General Engineering 02 engineering and technology Scientific literature Computer Science Applications Set (abstract data type) 020901 industrial engineering & automation Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Point (geometry) Decision model Shadow (psychology) |
| Zdroj: | Expert Systems with Applications. 159:113536 |
| ISSN: | 0957-4174 |
| DOI: | 10.1016/j.eswa.2020.113536 |
| Popis: | It has been more than 20 years since the appearance of the Analytic Network Process (ANP) in the scientific literature. Since that time, this method has been used to address complex decision-making situations and capture the dependency and feedback among the different elements in the decision model. Yet, a review of ANP studies published in 2015 shows that the reports of these studies are either deficient or incomplete in the analysis or reporting to the point that it casts a shadow on the validity of their conclusions. We propose, to our knowledge for the first time, a set of best practices to conduct, analyze and report ANP studies. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect